Renewable energy is an essential part of striving for sustainable operations across industries. Predictive maintenance is one tool that helps build a reliable renewable energy infrastructure. With the ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

In his research, Komaragiri has leveraged machine learning models and neural networks for developing predictive maintenance frameworks that can identify anomalies, analyze data in real-time, and ...

In AIoT-based systems, sensors continuously collect high-frequency data such as vibration, temperature, pressure, and electrical signals. These data streams are processed by machine learning and deep ...

The software tool developed by Stony Brook University uses self-supervised learning to detect long-term solar equipment damage weeks or years before manual inspections find it.

Traditional vibration analysis falls short for slow-speed machinery. Augury’s AI-powered platform uses high-frequency ultrasound to deliver real-time diagnostics and predictive insights for low-RPM ...

The waste collection industry generated $69 billion in revenue in 2024, accounting for over two-thirds of the total US waste and recycling revenue. Logistics is the cornerstone of this industry, given ...

MaintainX reports a rise in predictive maintenance adoption and AI usage, though challenges like aging equipment and cost ...

Predicting exactly how and when a process tool is going to fail is a complex task, but it’s getting a tad easier with the rollout of smart sensors, standard interfaces, and advanced data analytics.

What is predictive maintenance (PdM)? It’s the application of instrumentation and intelligence to help determine the condition of equipment and whether maintenance should be performed to avoid ...